Dosimeters including lensless imaging systems

ABSTRACT

Among other things, a method comprises imaging a sample displaced between a sensor surface and a surface of a microscopy sample chamber to produce an image of at least a part of the sample. The image is produced using lensless optical microscopy, and the sample contains at least blood from a subject. The method also comprises automatically differentiating cells of different types in the image, generating a count of one or more cell types based on the automatic differentiation, and deriving a radiation dose the subject has absorbed based on the count.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application and claims priority under35 U.S.C. § 120 to U.S. patent application Ser. No. 15/943,595, filed onApr. 2, 2018, which is a continuation application of U.S. patentapplication Ser. No. 15/627,866, filed Jun. 20, 2017, which claims thebenefit of U.S. patent application Ser. No. 14/572,164, filed Dec. 16,2014 (Issued as U.S. Pat. No. 9,910,254 on Mar. 6, 2018), which claimsthe benefit of U.S. Provisional Patent Application 61/917,195, filedDec. 17, 2013. All of the applications named in the prior sentence areincorporated here by reference in their entireties

This application is also related to U.S. patent applications Ser.61/255,781, filed Oct. 28, 2009; Ser. No. 12/913,639, filed Oct. 27,2010; Ser. No. 13/095,175, filed Apr. 27, 2011; 61/761,467, filed Feb.6, 2013; 61/785,762, filed Mar. 14, 2013, and 61/839,735, filed Jun. 26,2013. All of the applications named in the prior sentence areincorporated here by reference in their entireties

This disclosure relates to dosimeters including lensless imagingsystems, and methods and systems associated with the dosimeters.

In some approaches, biological responses to radiation dose, orbiodosimetry, are measured by analyzing chromosome abnormalities, suchas dicentrics and ring forms in peripheral blood lymphocytes.Alternatively or in addition, the measurement can also be performed bydetecting radiation-induced free radicals in tooth enamel, e.g., usingelectron paramagnetic resonance.

In other approaches, biodosimetry is performed by monitoringdose-dependent, radiation-induced lymphopenia, neutropenia, leukopenia,thrombocytopenia and/or pancytopenia that develop over hours or daysafter radiation exposure. Typically, the monitoring is performed byskilled technicians using complex instrumentation. In some situations,flow cytometers and microscopes can be used for associated hematologicalanalyses.

SUMMARY

In general, in an aspect, a method comprises imaging a sample displacedbetween a sensor surface and a surface of a microscopy sample chamber toproduce an image of at least a part of the sample. The image is producedusing lensless optical microscopy, and the sample contains at leastblood from a subject. The method also comprises automaticallydifferentiating cells of different types in the image, generating acount of one or more cell types based on the automatic differentiation,and deriving a radiation dose the subject has absorbed based on thecount.

In general, in another aspect, an apparatus comprises a lensless imagingsystem and a processor. The lensless imaging system comprises an arrayof sensors having a common sensor surface and a microscopy samplechamber. The chamber comprises an upper surface. A space between theupper surface and the sensor surface is to receive a sample for imaging.The processor is configured to automatically receive an image of atleast a part of the sample generated by the lensless imaging system. Thesample contains at least blood from a subject. The processor is alsoconfigured to automatically display information associated withradiation dose absorbed by the subject.

Implementations of the methods and/or apparatuses may include one or anycombination of two or more of the following features. Generating a countof one or more cell types comprises generating a count of lymphocytes.Lymphocyte depletion is estimated based on the count of lymphocytes. Thesample is a first sample taken at a first time from the subject andcount for lymphocyte is a first count for lymphocyte, and a secondsample taken at a second, different time from the subject is imaged, asecond count of lymphocyte is generated based on the second sample, andlymphocyte depletion based on the first and second counts of lymphocyteis estimated. The sample contains fiduciary beads distributed amongblood cells of the sample. The cells of different types aredifferentiated based on one or more of color, size of cell, nuclearshape, and nuclear size. The count of one or more cell types isgenerated with correction for a volume of the imaged sample. The samplecontains diluted blood from the subject, and the count of one or morecell types is generated with correction for dilution of the blood. Thesample contains one or more of anticoagulant, diluent, stain, antibody,erythrocyte lysing solution, and other reagents. Generating a count ofone or more cell types comprises generating the count based on detectionone or more surface antigens associated with the one or more cell types.The imaging is performed without using a lens. The imaging comprisesimaging at a resolution of 1 mega pixels or higher. The imagingcomprises rapid remixing and resampling the displaced sample by raisingand lowering the surface of a microscopy sample chamber. The imagecontains information about cells distributed in no more than a monolayerlayer in the sample. The array of sensors is formed in a CMOS chip. Eachsensor of the array of sensors has a size of about 2 μm by 2 μm orsmaller. The processor is configured to automatically analyze datacontained in the image. Automatically analyzing the data comprisesclassifying different types of cells in the image. The processor isconfigured to generate a count of one or more cell types. The processoris configured to derive the radiation dose the subject has absorbedbased on the count. The processor is configured to automatically deliverthe received image to a machine external to the apparatus for themachine to process information contained in the image and provideinformation about the radiation dosage. There is a network interface forconnecting the apparatus to a network through wire or wirelessconnections. The apparatus is a handheld device. The sensors comprisedigital image sensors capable of lensless optical microscopy.

Implementations may provide one or more of the following advantages.Dosimeters, including lensless imaging systems can provide rapid,point-of-care determination of radiation doses absorbed by subjectsafter radiation exposure. The devices can be operated by a patient forself-assessment or in the field by unskilled operators without specialtraining. The dosimeters are compact in size and are portable, e.g., inpockets. They are made at a low cost, permitting wide and quickdeployment, e.g., for fast triage of large populations. The dosimetersimplement platform optical microscopy technology and are suitable foradditional capabilities, such as counting of any type of normal bloodcell, detection of abnormal blood cells or parasites, and chemicalanalysis of blood or other fluids. Modifications to or services of thedevices can be readily performed, even in the field. The samples for usewith the dosimeters can be readily prepared, e.g., collected from afinger of the patient and prepared using a pipette with pre-loadedmaterials, and transferred to the dosimeter at a high rate, e.g., atless than one minute per sample. The throughput of the dosimeter use canbe high, e.g., 30 tests or more per hour.

Other features, objects, and advantages of the invention will beapparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic side view partly in section of a system to detectand use light representative of a sample.

FIG. 2 is a schematic sectional side view of elements useful to detectand use light representative of a sample.

FIG. 3 is a schematic block diagram of a dosimeter.

FIG. 4 is a flow diagram.

FIG. 5A is an enlarged view of a portion of an image field of a bloodsample before the cells in the sample are classified.

FIG. 5B is an enlarged view of a portion of an image field of a bloodsample showing classified cells.

FIG. 6 is a linear regression analysis of lymphocyte counts of bloodsamples as determined by a dosimeter of this disclosure, plotted againstlymphocyte counts of the same blood samples measured by a currenthospital standard instrument.

The figures and elements shown in them are not always to scale and manyof them are illustrated schematically. The spatial relationships of theelements in the figure may appear differently than the descriptions inthe text, for example, above and below and top and bottom may be shownoppositely in the figures from the way they are described in the text.

DETAILED DESCRIPTION Overview

Accidents involving a nuclear reactor or transportation of radioactivematerials, as well as terrorist actions, could expose a large populationto hazardous, potentially lethal, radiation. In such events, it would bedesirable to determine quickly which individuals in that populationrequire urgent medical treatment. To conduct a triage for a largepopulation, e.g., many tens or hundreds of thousands, or even ofmillions of people, the radiation dose absorbed by each individual needsto be estimated rapidly and efficiently, using a device having a highthroughput, possibly even by untrained operators. One possible way toachieve the estimation, at least in part, is through biodosimetry, i.e.,measuring biomarkers in accessible tissues of individuals, the levels ofwhich have a quantitative relation to the absorbed radiation doses.Examples of such biomarkers include radiation-induced free radicals intooth enamel, which can be measured by electron paramagnetic resonance(EPR), onset of clinical signs such as vomiting, incidence of chromosomeabnormalities or histone phosphorylation in peripheral blood leukocytes,and changes in absolute count of various cell types in peripheral blood.

Among the radiation biomarkers, depletion of lymphocytes is highlycorrelated with chromosome abnormalities and tooth enamel EPR, and is areliable radiation biomarker. The depletion of lymphocytes in peripheralblood can be measured robustly and reliably for radiation doseestimation.

A dosimeter of this disclosure counts lymphocytes in peripheral bloodand provides rapid, early, and accurate triage for a large population.The dosimeter can be compact and portable, e.g., handheld. For example,the dimensions of the dosimeter are about 20 cm×12 cm×5 cm. Thedosimeter is easy to use and provides reliable results in a short periodof time, e.g., minutes. In some examples, the dosimeter automaticallycounts lymphocytes and total white blood cells from a finger prick ofwhole blood at the point of care, and outputs the counts and/or a screenresult, e.g., an indication of whether or not the individual beingmeasured needs to be treated, in 2 minutes or less. The dosimeter cansend an indication to an operator when the dosimeter determines based onthe measurement that the person being measured has been exposed toradiation exceeding a predetermined threshold, e.g., 2 Grey (Gy) ormore. The indication can contain detailed cell counts and/or radiationdosage information. However, in some situations, the indication can beas simple as whether or not the person being measured needs furthermedical care. The indication can have various forms, e.g., visual oraudio. As a result, the dosimeter can be used by health careprofessionals or by untrained persons. The dosimeter can also berelatively inexpensive so that a large number of them can be distributedto increase the speed of population triage. In emergency radiationexposure situations, there is also the likelihood that a significantnumber of unexposed individuals are presented to the triage site,demonstrating similar symptomology. Multiple, e.g., hundreds of,thousands of, or even more, dosimeters can be distributed in the fieldto professionals and/or non-professional local responders to carry outhigh-throughput triage. Individuals who need treatment due to theradiation exposure can be identified within a brief therapeutic windowfor effective treatment. Sometimes the individuals are equipped with thedosimeter and can conduct self-assessment.

Referring to FIG. 3, a dosimeter 300 includes a lensless imaging system302 and a processor 304 in communication with the lensless imagingsystem 302. The processor 304 may execute one or more algorithms forcontrolling the lensless imaging system 302 and for analyzing the image,e.g., detecting and classifying cells automatically, or plottinglymphocyte depletion curves following radiation exposure based onpreviously published data. Optionally, the dosimeter includes a database308 that stores the published data and other data for performing thedata analysis. The result of each analysis can also be stored in thedatabase 308 for later use, e.g., for statistical studies. In someimplementations, subject identifiers for the analyses, such as name,social security number, etc. can also be stored in association with eachanalysis. In some implementations, the results of the analyses can alsobe stored in a database remote to the dosimeter, e.g., on a computer.The data can be entered into such a database directly from thedosimeter, or through a touch screen or a keypad, or by voice recording,e.g., with speech recognition software. The dosimeter 300 can include anetwork interface, e.g., a USB port, a wire connection, or a wirelessconnection, such as Internet connection, so that the dosimeter 300 canconnect to a network or another machine. Data can be downloaded fromand/or uploaded to the dosimeter 300. Also optionally, the dosimeter 300includes a user interface 306, e.g., a display and an input mechanism,through which an operator interacts with the dosimeter 300.

In some implementations, alternative to or in addition to controllingthe imaging system and/or analyzing data, the control and/or the dataanalysis can also be performed external to the dosimeter 300. Forexample, the dosimeter 300 can connect, e.g., wirelessly, to an externalprocessor, e.g., a computer or a smart phone, that implements the one ormore algorithms that control the lensless imaging system and/or analyzethe data. The algorithms can be distributed to the external processor,e.g., through network distribution such as emails or website downloads,or through hardcopies such as CDs. The external processor can be localto the dosimeter 300, e.g., a smart phone or a tablet of an operator, sothat the external processor can be connected to the dosimeter throughwire or wirelessly. The external processor can also be remote to thedosimeter 300, e.g., a remote server. The remote server can be backedwith one or more large databases for use in precise measurement. Usingthe external processor, components of the dosimeter, such as theprocessor 304, the database 308, and/or the user interface 306 can besimplified or even eliminated, such that the cost, weight, and/or sizeof the dosimeter are reduced. For example, a dosimeter that isconnectable to a laptop computer using USB ports for operation can havea size of about 8 cm×5 cm×6 cm or smaller.

The lensless imaging system 302 has a digital image sensor architecturethat is capable of performing massively parallel, near-field opticalmicroscopy. An example of the digital image sensor is CMOS imagesensors, the details of which are explained further below. The CMOSimage sensors can be arranged in arrays. The resolution of the sensorsis not limited by diffraction, but instead is determined by the size ofthe near-field aperture (i.e., the pixel). The CMOS sensors can have ahigh imaging resolution, e.g., 1.4 μm square pixels, 1.1 μm squarepixels, 0.9 μm square pixels, or even higher. The system 302 does notrequire scanning, focusing, or other moving parts.

In use, a specimen, or a sample, of blood is placed close to or on thesensor surface. The lensless imaging system 302 images a monolayer offresh blood cells with sufficient resolution to identify the mostrelevant cell classes over a small area, e.g., 10 mm², that containssufficient numbers of cells for useful analysis. The samples for theanalysis can be relatively small, e.g., 10 μL, 1 μL, or even less. FIG.4 shows an example process of imaging the blood sample using thelensless imaging system. Initially, blood samples are taken (402), e.g.,from a standard lancet finger prick using disposable capillary pipettesprovided with the dosimeter. The pipettes are preloaded with apre-determined amount of stain and/or other reagents so that the bloodis stained when discharged from the pipettes. The sample containing thestained blood is then discharged (404) into to a sensor chamber of thedosimeter. The chamber is closed and the imaging system images (406) thesample. In some examples, individual full-field images at fullresolution, e.g., 8 million pixels, can be obtained in approximately0.05 seconds. The lensless imaging system 302 then outputs (408) data,e.g., data that represents the images, to an internal or externalprocessor for analysis. One example of the data analysis is improvingthe image quality by a variety of computational means, e.g., bycombining multiple sequentially obtained images according to methodsknown in the art, for example, as described in Milanfar P (2010)Super-Resolution Imaging (CRC Press, Boca Raton, Fla.), the entirecontent of which is incorporated here by reference.

Example Lensless Imaging Systems

As shown in FIG. 1, in some implementations of the concepts that wedescribe here, a system 100 can capture high resolution images (e.g.,full-color, gray-scale, “black-and-white” or a combination of them) of asample 101 (e.g., a sample in a gas phase, a liquid phase, or a solidphase, or a combination of those or other forms) that is in contact with(or in close proximity to) a light sensor 102. The light sensor includesa two-dimensional arrangement of light sensitive elements 105 that cancorrespond to an array of pixels in the image. We sometimes refer to theelements of the light sensor as pixels for simplicity

We sometimes use the phrase “light sensitive locations” in the broadestsense to include, for example any features of a device that areseparately sensitive to light or separately capable of emitting light,or both, including light sensitive elements or pixels and light sourcelocations. We sometimes use the phrase light source locations to referto elements capable of emitting light. In some cases we use the phraselight sensitive location to refer to an exposed light sensitive portionof a feature of the device without any covering, protective layer,shield, or any other feature that might separate the light sensitivefrom the ambient or from a sample.

We sometimes use the phrase “contact microscope” or “contact microscopy”to refer in the broadest sense to any device (or technique) thatincludes (a) a high resolution sensor of closely spaced light sensitiveor a high resolution set of light emitting locations that are exposed tothe ambient at a surface of the device together with (b) a device toassociate with that surface a portion of a sample that is to be imaged,and, in the case of light emitting locations, a light detectorrelatively far from the light emitting locations and sample, so that theportion of the sample is in contact with (or nearly in contact with) thesurface and a usable high resolution image can be obtained by the sensorwhen the portion of the sample is in place.

In contact microscopy, the sample is either in direct contact with thelight sensitive features of the sensor, or light emitting features ofthe light source, without any intervening material, or the sample may benearly in contact with the light sensitive or emitting features. Bynearly in contact, we mean, not in direct contact. However, thecloseness between the sample and the light sensitive or emittingfeatures may vary based on one or more factors, including the type oflight. For example, in some cases this may mean within the near field ofthe features, i.e., at a distance that is within ½ of the wavelength ofthe light involved or possibly at a distance that is within a wavelengthof the light involved. In another example, when illuminated withcollimated light, the specimen can be several micrometers away from thesensor surface while yielding good quality images. For someapplications, the distance can be up to tens of micrometers whileproducing good quality images.

We use the concept of a device to associate the sample with the surfacein its broadest sense to include any mechanism of any kind thatfacilitates the movement, flow, delivery, placement, or presentation,for example, of a portion of the sample into contact with or nearly intocontact with the light sensitive locations, including any mechanism thatuses mechanical, electrical, electromechanical, acoustic, magnetic,pneumatic, hydraulic, gravitational, inertial, or other features, forexample.

Sometimes the amount of sample loaded onto the sensor is larger than theamounted needed for imaging. In some implementations, the sample needsto be in the form of a relatively thin layer, e.g., 1 μm to 100 μm, orhave a thickness such that a single layer of cells of the sample isdispersed on the sensor for imaging. A lid or cover or chamber orchamber top 95 can be moved (or can descend) to contact the sample andadjust the amount of sample, e.g., the thickness of the sample, on thesensor. As an example, the adjustment can be done by pressing one end ofthe chamber top 95 against the sample 101 so that the excessive amountof sample flows out of the perimeters of the sensor 102. The chamber topcan also descend in other manners. We sometimes refer to the space thatis between the surface of the chamber top 95 that has completed itsdescent and the sensor surface 102 and in which the sample is located asa chamber.

The sensor can also include other components either as part of or inaddition to the light sensitive elements, to drive or read the elements,generate, process, or deliver signals to and from the elements, andperform other functions. Generally, when we refer to the sensor we meanthe integrated circuit or part of it that (a) receives light (orsometimes emits) at light sensitive elements and generates signals ordata representing the intensities of light detected by the lightsensitive elements, and (b) any electronic elements that directly drivethe light sensitive elements or cause the light-generated signals ordata to be delivered by the light sensitive elements, but not (c) anyother circuitry used to process the signals or data to form the image.

The sensor 102 can be part of or formed on an integrated circuit chip104, which can be made in a homogeneous fabrication mode or a hybridfabrication mode. The chip 104 can be mounted on a headboard 106, andthe headboard 106 can be part of or be connected to a control unit 108.In some applications, a lid or cover or chamber or chamber wall 95 canabut, touch, surround, enclose, or contain the sample or a portion of itwithin a space or chamber adjacent to an exposed surface 103 of thesensor or a portion of the headboard or both.

The control unit 108 can be part of or connected to a user device 110.The user device 110 can provide an interface 109 with a user 115; canreceive commands 111 and information 113 through the user interface fromthe user, process them, and forward them to the control unit 108; andcan receive information 117 from the control unit, process it, andprovide it to the user through the user interface. In some instances,the user interface can operate through the control unit 108 or theheadboard 106 or a combination of them and of the user device. Andcommands and information 111, 113, and 117 can be passed between any twoor more of the components.

The system can also include sample transport and management devices 131,133, that can include mechanical, electrical, or electronic componentsor combinations of them that enable or cause the sample to be deliveredto the sensor, held at the sensor, and removed from the sensor, asneeded. The devices 131, 133, can also process the sample before andafter imaging including by mixing materials with the sample, removingmaterials from the sample, fetching the sample from a source, disposingof the imaged sample, and any other function that may be needed withrespect to the sample in order to operate the system to perform theimaging.

The user device 110 can be a smart phone, another kind of handhelddevice, an instrument, a system, a manufacturing component, a workstation, or any other user device including one that is dedicated to thefunction of interacting with the control unit or one that has functionsnot limited to interaction with the control unit, or a combination ofthe two.

A complete working system or commercial product or component need notinclude all of the sensor, the chip, the headboard, the control unit,and the user device, but could include a combination of any two or moreof them.

In various implementations, any combination of two or more of the sensor102, the chip 104, the headboard 106, the control unit 108, and the userdevice 110 can have a variety of mechanical and electrical connectionsamong them. In addition, mechanical, fluid flow, electronic, software,data processing, communication, storage, and electrical functions neededfor various operations can be distributed in a variety of ways betweenand among pairs and three or more of those parts of the system. Thedistribution of functions can be arbitrary or based on commercial andtechnological considerations in a wide variety of ways.

In some instances, the sensor 102, which we use to refer to the lightsensitive area of the chip 104, can operate as a charge-coupled device(CCD) or as a complementary metal-oxide semiconductor (CMOS) sensor.Other imaging regimes may be possible. As mentioned earlier, in someexamples, the sensor is pixelated, that is, operates with respect torows and columns (or other array arrangements) of light sensitivepicture elements (pixels) 105.

During operation, the sensor responds to incident electromagneticradiation (e.g., light) 99 that passes through 1010, is scattered from,or emanates from the sample 101. Light that passes through or isscattered from or emanates from the sample may be altered in wavelength,for example, as it passes through or is scattered or emanates. Theincident electromagnetic radiation 99 and the transmitted, scattered, oremanated radiation is typically in the wavelength range of visiblelight, near ultraviolet, or near infrared. We use the term light in itsbroadest sense to include all such ranges, for example.

Because the sample 101 is in contact with or essentially in contact withor in close proximity to the surface 103 of the sensor, there may be noneed for any optical elements to be used in the system to refract orcollimate or redirect the light from the sample to the sensor.

Light from a portion 107 of the sample that is adjacent to a pixel (oris in a path between the incident light 99 and the pixel) will bereceived largely (in some cases essentially entirely) by that pixel 105.

In this arrangement, the light sensed by the array of pixels of thesensor is directly representative of a corresponding array of portionsof the sample and therefore represents in effect an image of the sample,an image that can be of high resolution.

To the extent that the initial source of the light reaching the sensorsis in the environment, that light may be ambient light or can beprovided by a dedicated light source 119. In some implementations it maybe useful to control the illumination of the sample and in particularthe uniformity or orientation of the illumination by controlling thelight source or screening out ambient light or both.

To capture an image of the sample, the sensor is driven and read duringa conceptual image capture cycle. During an image capture cycle, thelight received by the sensor at all of its pixels is converted toelectrical signals (e.g., analog signals or digital values) that aredelivered to electronic components of the chip. The signals may be readin parallel or serially depending on the technology. The electricalsignal from each of the pixels typically is represented by a quantizedintensity value corresponding to the intensity of light sensed by thepixel, within some range such as a range represented by 14-bit digitalvalues. Color information can be obtained in a variety of ways, forexample, using different band-pass optical filters systematicallyarrayed over adjacent pixels, or sequential imaging with different colorillumination, and possibly in other ways. Whatever method is used, theelectrical signals that are received from the various pixels in spaceand/or time together can represent a full-color high-resolutionhigh-dynamic range image of the sample.

In addition to the electronic features of the system, there aremechanical elements discussed below that among other things handle,contain, and illuminate the sample 101.

Some or all of the electronic and mechanical components that form thesystem, including the sensor, the chip 104, the headboard 106, thecontrol unit 108, the user device 110, and the user interface 109, andcombinations of any two or more of them can be produced as individualcommercial products and can be either reusable or disposable.

For high resolution imaging, a monolayer of each sample is imaged. Themonolayer imaging can be achieved by controlling the sample volumesloaded onto the sensors. Examples of such control include sampleprocessing before loading the sample onto the sensors, mechanicalcontrol using the chamber of the lensless imaging system 100 after thesample is loaded into the chamber, and/or the combination of both.

Referring to FIG. 2, the sample 101 (we sometimes use the word specimeninterchangeably with the word sample) that is being imaged can becomposed of or include small similar types of units 97, such asparticles, bits, specks, organisms, cells, or molecules, or combinationsof them or combinations of any two or more of the different types. Theunits 97 may be suspended in or carried in a liquid 104 to formliquid-suspended sample units 97, entrained in a gas to formgas-suspended sample units (not shown), rest in an unsuspended andun-entrained form (a powder, for example) on the surface of the sensor(not shown), or be held in an integrated matrix of solid, gelled, orother integral self-supporting material, such as a sectioned layer oftissue, to name only a few examples. We sometimes use the term matrixvery broadly to include, for example, any material in which sample unitsare held, including liquid, gas, solid, gel, or any other material.

Additionally, the sample 101 can also contain spacing features 230 forcontrolling the volume of the sample 101 on the sensor 102. In someinstances and for a given kind of sample unit or a precisely specifiedvolume of sample (e.g., for a blood count, or other analysis in whichthe number of sample units is to be counted for a precise volume of thesample), the volume of the sample imaged by the sensor is preciselycontrolled by the width and length of the top active imaging surface ofthe sensor and by the height of the gap 220 (or the chamber) betweenthat surface and the flat bottom surface of the chamber top. In somecases, the volume may not need to be precise, but the gap height mayneed to be a precise amount, or no larger than a certain amount, or nosmaller than a certain amount, or a combination of those conditions.

A wide variety of techniques and devices can be used to form andmaintain a height (e.g., a precise height) of the gap. We broadly referto those techniques and devices as spacing features. In the exampleshown in FIG. 2, the spacing feature includes microspheres or otherkinds of beads of uniform size, say, 1.0 μm or 3.0 μm or 5.0 μm. Toestablish a precise and uniform spacing and therefore volume of thesample space, it may be useful to specify the precision of the beadsizes, for example, the beads could be specified as 2.0 μm with aprecision of plus or minus 100 nanometers. The beads can benon-spherical. The beads can be used in a variety of different ways.

As shown in FIG. 2, in some implementations, the beads 230 are includedwithin the sample, for example a sample having a liquid matrix in whichsample units (which may be smaller than the beads) are suspended, whenthe sample is delivered to the sensor surface 103. If the chamber top isthen allowed to settle on or be pressed down onto the sample, andassuming that there are enough beads in the sample and they arereasonably well distributed within the liquid, then a uniform accurategap height can be achieved. For this purpose, the beads might be presentin the sample at a concentration of 10,000-500,000 beads per microliterof sample, for example. Maintaining an even distribution of the beads inthe sample can be done by simple mechanical agitation if the beads areselected to have close to neutral buoyancy in the sample.

In some cases, the beads can be roughly the same size as the sampleunits. In some implementations, beads of two different sizes can beincluded. A larger size defines the intended spacing. A smaller size canbe counted to verify that the volume of the sample space is as intended,assuming the smaller beads are distributed through the sample reasonablyuniformly, and the number of smaller beads per unit volume of the sampleis known. The beads may be transparent in order to allow light to passthrough to the sensor, or may be colored, or fluorescent, or opaque, ora combination of two or more of those characteristics.

After a sample is loaded into the chamber, the chamber top can belowered relative to the sensor surface 103 to remove the excessivevolume of sample from the sensor 102 and allow the sample units 97 (suchas cells that are disbursed in a fluid) to be evenly distributed overthe surface 103 of the sensor 102. In some implementations, the removalof the excessive volume does not alter the bulk concentration of thesample units so that the imaging of a relatively small volume of thesample, e.g., about 1 produces data applicable to the bulk sample, e.g.,about 40 μL or more, dispensed onto the sensor. In otherimplementations, the new concentration is consistently proportional tothe bulk concentration of the sample units, allowing for a correctionfactor to be determined. To achieve the desired sample concentration forimaging, the sample can be further processed as described further below.

The chamber top can be lowered in various ways. In one example,referring again to FIG. 2, the chamber top has a flat top surface 400and during the lowering of the chamber top, the top surface 400 is keptsubstantially parallel to the top surface 103 of the sensor 102. Wesometimes call this process a flat, linear descent.

Example Dosimeters

A dosimeter, such as the dosimeter 300 of FIG. 3, including a lenslessimaging system, such as the system 100 of FIG. 1, can perform fast andreliable biodosimetry for self-assessment or by large numbers ofemergency health care providers without specialized training in thetechnology to triage a large population within one or two days of amajor radiation event. The dosimeter can be a pocket-sized device thatmeasures absolute counts of particular white blood cells for estimatingthe absorbed radiation dosage via lymphocyte depletion. The dosimetercan have high sensitivity, specificity, repeatability, andreproducibility. The turnaround time for the analysis process, e.g.,including at least steps 404, 406, 408 of the process 400 in FIG. 4, isa few minutes or less. The dosimeter is operable and outputs indicationsthat are readily understandable by people without extensive training inthe technical field, e.g., paramedics or other emergency care givers. Apatient can even use the dosimeter to conduct self-assessment. Thedosimeter can be powered by batteries or other power supplies and can beenergy efficient. For example, the dosimeter can run for at least 24hours without battery replacement or recharge. The device is reliablesuch that the mean time between failures is high, for example, many tensor hundreds of hours. The device can include self-diagnosticcapabilities to identify components that have failed, and suchcomponents can be readily replaced in the field. An operator caninteract with the dosimeter through a graphical user interface.

The dosimeter can be autonomous and be capable of computing, displaying,archiving, and wirelessly transmitting results with no external computerrequired for any aspect of operation. In addition, the dosimeterincludes sensor control electronics, illuminator, display, and reportingcomponents that can be addressed by electrical, mechanical, and softwareengineering.

The dosimeter can contain a CMOS chip that provides a sensor surface ofabout 8.25 mm² and includes 3280 by 2464 arrays of 1.1 μm pixel sensors,with good resolution and sampling statistics. The chip can collectsample images at video rate, e.g., about 24 full frames per second. Thechip may be relatively thin, e.g., about 200 μm to about 300 μm.Although not shown or discussed with respect to FIGS. 1 and 2, thelensless imaging system of the dosimeter can detect fluorescence. Forexample, the image sensor surface includes one or more layers offilters, which can include UV (ultra violet)-blocking filters that arecompatible with transmitted-light microscopy over visible wavelengths.Fluorescence imaging of the samples can then be performed, for example,by UV excitation. Fluorescence imaging may allow use of additionalbiodosimetry markers, such as levels of phosphorylation of histonegamma-H2AX in lymphocytes, which may be particularly valuable for earlymonitoring, e.g., less than 24 hours post-exposure, and low dosage,e.g., less than 1 Gy.

The one or more algorithms for controlling the lensless imaging systemand for analyzing the data output from the lensless imaging system canbe pre-developed. The algorithms may also be updated based on use of thedosimeter. In some implementations, published biodosimetry data, acuteradiation syndrome literature, and internally generated data are used todetermine dosimeter parameters for sample handling and data analysise.g., for lymphocyte and other blood cell-based hematologicalbiodosimetry. The parameters can be further analyzed and validated usingexisting samples to confirm that detectability and reliability of thedosimeter are adequate for triage purposes. In some implementations, theanalysis and validation processes may identify potential interferingsubstances and conditions that could confound the interpretation ofresults from the dosimeter.

In addition to the dosimeter, to facilitate the blood sampling andimaging, a pipette system for sample collection, transfer, and additionof reagents, antigens and/or volume fiduciary microbeads can be providedto the dosimeter operator. Reference bead suspensions for systemcalibration can be taken into consideration in the algorithms thatcontrol the lensless imaging system and analyze data to improve accuracyof cell classification.

In some implementations, accuracy of cell classification can also beenhanced by immunologically detecting specific surface antigens, forexample, CD3 and CD19, to detect T and B lymphocytes. Further to thesample processing discussed above, e.g., adding reagents, staining,and/or adding microbeads, before imaging, fluorescent ormicrobead-labeled antibodies directed against surface antigens such asCD3 and CD19 are added to a processed sample. Such an addition canrender the classification of lymphocytes in the blood sampleunambiguous, as the lymphocytes are rendered fluorescent or “decorated”with the microbead-coupled antibodies. The antibodies can also beincluded in the pipette system. However, the addition may increase theoverall cost and sample handling complexity.

In use, referring again to FIG. 4, a blood sample is taken (402) byapplying a standard lancet to the subject's cleaned, e.g., usingdisposable alcohol swab, finger tip. Sequential drops of blood areexpressed according to standard practice. To transfer (404) the sample,a transfer device takes up a portion of a drop, which may be as littleas 5 μl or as much as 50 μl. The transfer device may be a volumetricpipette, a calibrated capillary tube, a micropipette or other similardevices. In some implementations, the portion is a portion of a thirddrop of the sequential drops. Taking the measurement from the third dropmay improve measurement precision. The transfer device may be preloadedwith anticoagulant, diluent, stain, antibody, fiduciary beads,erythrocyte lysing solution and/or other reagents. Alternatively, one ormore of these materials may be added to the blood sample by one or moreother pipettes, in predetermined volume(s) proportion to the volume ofblood. The blood, diluted with such reagents or not, is transferred tothe chamber of the lensless imaging system, and is illuminated andimaged (406). The volume of the imaged blood is determined by priorcalibration of the chamber dimensions, by inclusion and counting offiduciary beads added to the blood at a known concentration, and/or byother means.

One or more algorithms, e.g., in the form of computer vision software,are then used to analyze the data output (408) from the lensless imagingsystem. For example, the algorithm(s) identify lymphocytes among theimaged particles in the blood, on the basis of color and size of cell,nuclear shape and size, and/or other parameters. As an example, FIG. 5Ashows a portion of an imaged field 500 of a blood sample. FIG. 5B showserythrocytes 502 and leukocytes 504 that are automatically classifiedand labeled (with circles) by the software. Absolute lymphocyte count isthen determined based on the classified cells, such as those shown inFIG. 5B, which may be corrected based on the volume and dilution of theimaged blood sample, if any. An example showing the accuracy of thelymphocyte counts determined by a dosimeter of this disclosure is shownin FIG. 6. A linear regression analysis of such lymphocyte counts ofblood samples as determined by a dosimeter of this disclosure is plottedagainst lymphocyte counts of the same blood samples measured by acurrent hospital standard instrument.

If the time from radiation exposure to blood sampling is known, a singlelymphocyte count may be used to estimate a depletion rate of lymphocyte,and thus an absorbed radiation dose, assuming pre-exposure count wasnormal average. In some implementations, the lymphocyte depletion isdetermined based on the count of lymphocytes with reference to normalcount in similar individuals. In an example, the reference normal countcan be 2.45×10⁹ cells/L. The reference normal count can be corrected forage, sex, etc. The normal average is generally known. See, for example,The Medical Basis for Radiation Accident Preparedness, K F Hubner, S FFry, eds, Elsevier North Holland Inc., 1980, 297-310, and Annuals ofInternal Medicine, 2004, vol 140:1037-51.

In some implementations, more accurate estimates can be achieved byobtaining a second blood sample from the same individual after aninterval of several hours. In some implementations, even more bloodsamples can be taken and analyzed. The lymphocyte depletion rate can becalculated based on the following model (see, e.g., “Acute RadiationSyndrome Treatment Guidelines,” Radiation Injury Treatment Network,September 2010;http://www.ritn.net/WorkArea/DownloadAsset.aspx?id=2147483696, theentire content of which is incorporated here by reference):

Lt=2.45×10⁹ /L×e ^(−k(D)t)

where Lt equals the lymphocyte count, 2.45×10⁹ cells/L equals a constantrepresenting the consensus mean lymphocyte count in the generalpopulation, k(D) equals the lymphocyte depletion rate constant for aspecific acute photon dose D, and t equals the time after exposure(days). A calculator for dose estimation by these means is available atthe U.S. Department of Health and Human Services' Radiation EmergencyMedical Management website,http://www.remm.nlm.gov/ars_wbd.htm#lymphocyte.

In some implementations, the lymphocyte counts can be further correctedbased on known variation factors. For example, lymphocytes may notdistribute perfectly uniformly within a blood sample, and thenon-uniform distribution may lead to a difference between the actualnumber of lymphocyte and the counts produced by the dosimeter.Furthermore, the volume of the chamber in the lensless imaging systemmay also vary from test to test. As a result, the actual volume of asample being imaged may differ from sample to sample. The variationfactors can be statistically determined for correcting the lymphocytecounts.

An example of determining the variation factor originated from thechamber volume variation is explained as follows. The actual volume ofthe chamber is determined by counting fiduciary beads included with ablood sample at a known concentration for reducing errors due tovariations in chamber volume. Based on an assumption of 1,000 beads inthe blood sample, the variation in count due to random distribution is3.3% (1,000 beads, standard deviation of the count=32.85, coefficient ofvariation (CV)=3.3%). These two independent error sources (from thechamber volume and the bead count) result in a combined error of 8.9%.In some implementations, the surface area of the sensors is increasedand the aggregate volume error factor is less than 5%.

In some implementations, the analyzed volume is increased by reloadingsample into the chamber after the first data acquisition. The countingstatistics for rare cells (or particles) can be improved by introducinga new volume of sample. As the volume loaded (˜10 μL or more) is muchlarger than the volume actually monitored when the chamber top islowered into place (˜0.1 μL), a new volume of sample can be efficientlyreloaded by raising and lowering the chamber top a few times to mix thesample before re-lowering the chamber top into its “read” position. Therapid raising and lowering mechanism of the chamber top is a generallyuseful strategy for improving sampling statistics.

In some implementations, it takes approximately 30 seconds for sampletransfer and image acquisition (e.g., steps 404 and 406 of the process400 shown in FIG. 4), and approximately 120 seconds or less, e.g., lessthan 30 seconds or less than 15 seconds, for image processing andanalysis. Taking subject preparation and device cleaning into account,throughput of each dosimeter can be more than 30 tests per hour.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, in tangibly-embodied computer software or firmware, incomputer hardware, including the structures disclosed in thisspecification and their structural equivalents, or in combinations ofone or more of them. Embodiments of the subject matter described in thisspecification can be implemented as one or more computer programs, i.e.,one or more modules of computer program instructions encoded on atangible non-transitory storage medium for execution by, or to controlthe operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on an artificiallygenerated propagated signal, e.g., a machine-generated electrical,optical, or electromagnetic signal, that is generated to encodeinformation for transmission to suitable receiver apparatus forexecution by a data processing apparatus. The computer storage mediumcan be a machine-readable storage device, a machine-readable storagesubstrate, a random or serial access memory device, or a combination ofone or more of them.

The term “data processing apparatus” refers to data processing hardwareand encompasses all kinds of apparatus, devices, and machines forprocessing data, including by way of example a programmable digitalprocessor, a digital computer, or multiple digital processors orcomputers. The apparatus can also be or further include special purposelogic circuitry, e.g., an FPGA (field programmable gate array) or anASIC (application specific integrated circuit). The apparatus canoptionally include, in addition to hardware, code that creates anexecution environment for computer programs, e.g., code that constitutesprocessor firmware, a protocol stack, a database management system, anoperating system, or a combination of one or more of them.

A computer program, which may also be referred to or described as aprogram, software, a software application, a module, a software module,a script, or code, can be written in any form of programming language,including compiled or interpreted languages, or declarative orprocedural languages, and it can be deployed in any form, including as astand alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment. A computer program may, butneed not, correspond to a file in a file system. A program can be storedin a portion of a file that holds other programs or data, e.g., one ormore scripts stored in a markup language document, in a single filededicated to the program in question, or in multiple coordinated files,e.g., files that store one or more modules, sub-programs, or portions ofcode. A computer program can be deployed to be executed on one computeror on multiple computers that are located at one site or distributedacross multiple sites and interconnected by a data communicationnetwork.

The processes and logic flows described in this specification can beperformed by one or more programmable computers executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit). For a system of one or morecomputers to be “configured to” perform particular operations or actionsmeans that the system has installed on it software, firmware, hardware,or a combination of them that in operation cause the system to performthe operations or actions. For one or more computer programs to beconfigured to perform particular operations or actions means that theone or more programs include instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the operations oractions.

Computers suitable for the execution of a computer program, by way ofexample, can be based on general or special purpose microprocessors orboth, or any other kind of central processing unit. Generally, a centralprocessing unit will receive instructions and data from a read onlymemory or a random access memory or both. The essential elements of acomputer are a central processing unit for performing or executinginstructions and one or more memory devices for storing instructions anddata. Generally, a computer will also include, or be operatively coupledto receive data from or transfer data to, or both, one or more massstorage devices for storing data, e.g., magnetic storage, magnetooptical disks, or optical disks. However, a computer need not have suchdevices. Moreover, a computer can be embedded in another device, e.g., amobile telephone, a personal digital assistant (PDA), a mobile audio orvideo player, a game console, a Global Positioning System (GPS)receiver, or a portable storage device, e.g., a universal serial bus(USB) flash drive, to name just a few.

Computer readable media suitable for storing computer programinstructions and data include all forms of non-volatile memory, mediaand memory devices, including by way of example semiconductor memorydevices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks,e.g., internal hard disks or removable disks; magneto optical disks; andCD ROM and DVD-ROM disks. The processor and the memory can besupplemented by, or incorporated in, special purpose logic circuitry.

Control of the various systems and processes described in thisspecification, or portions of them, can be implemented in a computerprogram product that includes instructions that are stored on one ormore non-transitory machine-readable storage media, and that areexecutable on one or more processing devices. The systems described inthis specification, or portions of them, can be implemented as anapparatus, method, or electronic system that may include one or moreprocessing devices and memory to store executable instructions toperform the operations described in this specification.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinvention or on the scope of what may be claimed, but rather asdescriptions of features that may be specific to particular embodimentsof particular inventions. Certain features that are described in thisspecification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable subcombination. Moreover, although features may be describedabove as acting in certain combinations and even initially claimed assuch, one or more features from a claimed combination can in some casesbe excised from the combination, and the claimed combination may bedirected to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various system modulesand components in the embodiments described above should not beunderstood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

Particular embodiments of the subject matter have been described. Otherembodiments are within the scope of the following claims. For example,the actions recited in the claims can be performed in a different orderand still achieve desirable results. As one example, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In some cases, multitasking and parallel processing may beadvantageous. In addition to uses in radiation exposure caused byaccidents, the dosimeters can also be used in radiation therapies, suchas treatment for cancer, and in experimental research.

1-32. (canceled)
 33. A method comprising: imaging a sample displacedbetween a sensor surface and a surface of a microscopy sample chamber toproduce an image of at least a part of the sample, the image beingproduced using lensless optical microscopy, the sample containing atleast blood from a subject; automatically differentiating cells ofdifferent types in the image; generating a count of one or more celltypes based on the automatic differentiation; and deriving a radiationdose the subject has absorbed based on the count.
 34. The method ofclaim 33, wherein generating a count of one or more cell types comprisesgenerating a count of lymphocytes.
 35. The method of claim 34,comprising estimating lymphocyte depletion based on the count oflymphocytes.
 36. The method of claim 34, wherein the sample is a firstsample taken at a first time from the subject and count for lymphocyteis a first count for lymphocyte, and the method comprises imaging asecond sample taken at a second, different time from the subject,generating a second count of lymphocyte based on the second sample, andestimating lymphocyte depletion based on the first and second counts oflymphocyte.
 37. The method of claim 33, wherein the sample containsfiduciary beads distributed among blood cells of the sample.
 38. Themethod of claim 33, wherein the cells of different types aredifferentiated based on one or more of color, size of cell, nuclearshape, and nuclear size.
 39. The method of claim 33, wherein the countof one or more cell types is generated with correction for a volume ofthe imaged sample.
 40. The method of claim 33, wherein the samplecontains diluted blood from the subject, and the count of one or morecell types is generated with correction for dilution of the blood. 41.The method of claim 33, wherein the sample contains one or more ofanticoagulant, diluent, stain, antibody, erythrocyte lysing solution,and other reagents.
 42. The method of claim 33, wherein generating acount of one or more cell types comprises generating the count based ondetection one or more surface antigens associated with the one or morecell types.
 43. The method of claim 33, wherein the imaging is performedwithout using a lens.
 44. The method of claim 33, wherein the imagingcomprises imaging at a resolution of 1 mega pixels or higher.
 45. Themethod of claim 33, wherein the imaging comprises rapid remixing andresampling the displaced sample by raising and lowering the surface of amicroscopy sample chamber.
 46. The method of claim 33, wherein the imagecontains information about cells distributed in no more than a monolayerlayer in the sample.
 47. The method of claim 33, wherein automaticallydifferentiating cells comprises automatically classifying differenttypes of cells in the image.
 48. The method of claim 33, comprisingautomatically delivering the image to a machine to process informationcontained in the image and provide information about the radiationdosage.
 49. The method of claim 33, comprising connecting to a networkthrough wire or wireless connections.
 50. The method of claim 33,comprising deriving the radiation dosage based on comparing a count ofthe one or more cell types to reference biodosimetry data for the one ormore cell types.
 51. The method of claim 33, comprising estimatinglymphocyte depletion based on one or more counts of lymphocytes.
 52. Themethod of claim 33, comprising determining a first count of a first typeof cells within a first sample received within the chamber at a firsttime; determining a second count of the first type of cells within asecond sample received within the chamber at a second time after thefirst time; and estimating the change in concentration of the first typeof cells based on comparing the first count to the second count.
 53. Themethod of claim 33, comprising correcting the count of the cells of atleast one type based on a volume of the sample.
 54. The method of claim33, comprising obtaining the sample by a pin prick of the subject. 55.The method of claim 33, comprising including in the sample microbeadscoupled to other molecules to endow the microbeads with bindingspecificity.
 56. The method of claim 33, comprising including in thesample microbeads of two or more different sizes.
 57. The method ofclaim 33, comprising including in the sample microbeads of two or moredifferent shapes.
 58. The method of claim 33, comprising including inthe sample microbeads that are at least one of transparent, colored,fluorescent, and opaque.
 59. The method of claim 33, comprising moving afirst surface of the chamber relative to the sensor surface.
 60. Themethod of claim 59, moving the first surface parallel to the sensorsurface during at least part of the motion.
 61. The method of claim 59,comprising moving the first surface to a designated location toward thesensor surface such that when the first surface is moved to thedesignated location, the part of the sample that is included in theimage includes cells distributed in no more than a monolayer in thesample.
 62. The method of claim 33, comprising generating the count ofthe cells of at least one type based on a volume of diluent within thesample.
 63. The method of claim 33, comprising generating the count ofthe cells of at least one type based on detecting one or more surfaceantigens associated with the cells of the least one type.
 63. The methodof claim 33, comprising mixing a volume of the sample received on thesensor surface by raising and lowering a surface of the chamber.
 64. Themethod of claim 33, comprises determining a degree of change inconcentration of the cells of the at least one type in the blood. 65.The method of claim 64 comprising, based on the degree of change in theconcentration of the cells of the at least one type in the blood,displaying information associated with a radiation dose absorbed by thesubject.